Curriculum Vitae and Publications Dr. Danilo Dessì

Danilo Dessì is a Post-Doctoral Researcher/Senior Researcher at FIZ Karlsruhe – Leibniz Institute for Information Infrastructure and Karlsruhe Institute of Technology (KIT), Institute of Applied Informatics and Formal Description Methods (AIFB) with Prof. Dr. Harald Sack. He holds a Master’s degree and a Doctoral degree from the Department of Mathematics and Computer Science of the University of Cagliari (Italy). His PhD thesis was supervised by Prof. Diego Reforgiato Recupero. He has been visiting researchers in the following centers all around the world: Philips Research (Eindhoven, 2016), Center for Data Science NYU (New York City, 2017), Knowledge Media Institute – The Open University (Milton Keynes, 2018), and Laboratoire d’informatique de Paris Nord – University of Paris 13 (Paris, 2019). The list of his publications are accessible on DBLP, Scopus, and Google Scholar. He is a member of the laboratory of Human-Robot Interaction HRI Lab@UNICA at the University of Cagliari (in collaboration with R2M Solution s.r.l.) whose research and development activities are dedicated to the understanding, designing, and evaluating of several robotic platforms which employ different research technologies (e.g. Sentiment Analysis, Semantic Web, Deep Learning, Natural Language Processing, etc.) when interacting with humans. His current research is funded by the MaterialDigital project whose goal is the digitalization of materials to build a powerful ontology for materials and transfer their associated processes to their manufacture into applications.

Program Committees

2020

• ISWC, 19th International Semantic Web Conference 2020, Research track
• CSSA, Combining Symbolic and Sub-symbolic methods and their Applications (CSSA), Co-located with CIKM 2020
• SKG, Scientific Knowledge Graphs Workshop co-located with TPDL 2020
• SAC, The 35th ACM/SIGAPP Symposium On Applied Computing, special Track on Knowledge and Language Processing, 2020
• BIAS, International Workshop on Algorithmic Bias in Search and Recommendation, held as part of the 42nd European Conference on Information Retrieval (ECIR 2020), 2020
• DL4KG, Workshop on Deep Learning for Knowledge Graphs, held as part of the European Semantic Web Conference (ESWC 2020), 2020

2019

• SEMANTiCS, Semantic Web Conference, Poster and Demo track, 2019
• SAC, The 34th ACM/SIGAPP Symposium On Applied Computing, special track on Knowledge and Language Processing, 2019
• CLIC-IT, Italian Conference on Computational Linguistics, 2019
• DL4KG, Workshop on Deep Learning for Knowledge Graphs, held as part of the European Semantic Web Conference (ESWC 2019), 2019

2018

• EMSASW, Workshop on Sentic Computing, Sentiment Analysis, Opinion Mining, and Emotion Detection, held as part of the European Semantic Web Conference (ESWC 2018), 2018

Conference and Workshops Chairs

2021

• Workshop Co-Chair of L2D 2021, the First International Workshop on Enabling Data-Driven Decisions fromLearning on the Web, collocated with the 14th ACM International Conference on Web Search and Data Mining (WSDM 2021)

Reviewer (International Journals and Conferences)

2020

• 2020-present: SWJ, Semantic Web Journal
• 2020-present: Future Generation Computer Systems

Editorship

Future Generation Computer Systems, ISSN: 0167-739X, Special Issue on Advances in Intelligent Systems for Online Education (to be published)

Zitate

Danilo Dessì @ Google Scholar
Danilo Dessì @ DBLP
Danilo Dessì @ Scopus

2020

• D. Dessì, F. Osborne, D. Reforgiato Recupero, D. Buscaldi, E. Motta: Generating Knowledge Graphs by Employing Natural Language Processing and Machine Learning Techniques within the Scholarly Domain. Future Generation Computer Systems Journal - Special Issue on Machine Learning and Knowledge Graphs (2020) (To be published) [local copy (PDF)]
• D. Dessì, F. Osborne, D. Reforgiato Recupero, D. Buscaldi, E. Motta, H. Sack: AI-KG: an Automatically Generated Knowledge Graph of Artificial Intelligence. In Proceedings of the 19th International Semantic Web Conference (ISWC 2020), Resource Track, pp. 127-143. DOI: https://doi.org/10.1007/978-3-030-62466-8_9 [local copy (PDF)]
• D. Dessì, R Helaoui, V. Kumar, D. Reforgiato Recupero, D. Riboni: TF-IDF vs Word Embeddings for Morbidity Identification in Clinical Notes: An Initial Study. In Proc. Proceedings of the First Workshop on Smart Personal Health Interfaces co-located with 25th International Conference on Intelligent User Interfaces (IUI 2020), 1-12. http://ceur-ws.org/Vol-2596/paper1.pdf
• S. Consoli, D. Dessì, G. Fenu, M. Marras (2020). Deep Attention-based Model for Helpfulness Prediction of Healthcare Online Reviews. In Proc. Proceedings of the First Workshop on Smart Personal Health Interfaces co-located with 25th International Conference on Intelligent User Interfaces (IUI 2020), 33-49. http://ceur-ws.org/Vol-2596/paper3.pdf
• F. Hoppe, T. Tietz, D. Dessì, N. Meyer, M. Sprau, M. Alam, H. Sack: The Challenges of German Archival Document Categorization on Insufficient Labeled Data, In: Proceedings of the 3rd Workshop on Humanities in the Semantic Web (WHiSe), Co-located with the 15th Extended Semantic Web Conference (ESWC 2020), CEUR workshop proceedings, Volume 2695, 15-20., CEUR-WS.org, online at http://ceur-ws.org/Vol-2695/paper2.pdf. [local copy (PDF)].
• D. Dessì, M. Dragoni, G. Fenu, M. Marras, D. Reforgiato: Deep Learning Adaptation with Word Embeddings for Sentiment Analysis on Online Course Reviews. In B. Agarwal, R. Nayak, N. Mittal, S. Patnaik: Deep Learning-Based Approaches for Sentiment Analysis- Algorithms for Intelligent Systems. Singapore: Springer, 2020, 57-83. DOI: https://doi.org/10.1007/978-981-15-1216-2_3

2019

• D. Dessì, G. Fenu, M. Marras, D. Reforgiato Recupero: Bridging learning analytics and Cognitive Computing for Big Data classification in micro-learning video collections, Computers in Human Behavior, Vol. 92, 2019, 468-477. DOI: https://doi.org/10.1016/j.chb.2018.03.004
• D. Reforgiato Recupero, D. Dessì, E. Concas: A Flexible and Scalable Architecture for Human-Robot Interaction, In Proc. of the 15th European Conference on Ambient Intelligence (AmI 2019), pp.57-83. DOI: https://doi.org/10.1007/978-3-030-34255-5_21
• D. Buscaldi, D. Dessì, E. Motta, F. Osborne, D. Reforgiato Recupero: Mining Scholarly Publications for Scientific Knowledge Graph Construction, In Proc. of 16th European Semantic Web Conference (ESWC 2019) Satellite Events, Poster and Demo Track, 8-12. DOI: https://doi.org/10.1007/978-3-030-32327-1_2
• D. Dessì, D. Reforgiato Recupero, G. Fenu, S. Consoli: A Recommender System of Medical Reports Leveraging Cognitive Computing and Frame Semantics. In G. Tsihrintzis,D. Sotiropoulos, L. Jain: Machine Learning Paradigms. Cham: Springer, 2019, 7-30. DOI: https://doi.org/10.1007/978-3-319-94030-4_2
• G. Bardaro, D. Dessì, E. Motta, F. Osborne, & D. Reforgiato Recupero: Parsing Natural Language Sentences in Robot Actions. In Proc. of the 18th International Semantic Web Conference (ISWC 2019) Satellite Tracks, Poster Track, 93-96. http://ceur-ws.org/Vol-2456/paper24.pdf
• D. Buscaldi, D. Dessì, E. Motta, F. Osborne, D. Reforgiato Recupero: Mining Scholarly Data for Fine-Grained Knowledge Graph Construction. In Proc. of the Workshop on Deep Learning for Knowledge Graphs (DL4KG 2019) co-located with the 16th Extended Semantic Web Conference 2019 (ESWC 2019), 21-30. http://ceur-ws.org/Vol-2377/paper_3.pdf
• D. Dessì, M. Dragoni, G. Fenu, M. Marras, D. Reforgiato Recupero: Evaluating neural word embeddings created from online course reviews for sentiment analysis. In Proc. of the 34th ACM/SIGAPP Symposium on Applied Computing, 2124-2127. DOI: https://doi.org/10.1145/3297280.3297620

2018

• D. Dessì, J. Cirrone, D. Reforgiato Recupero, D. Shasha: SuperNoder: a tool to discover over-represented modular structures in networks. BMC Bioinformatics, Vol. 19 (318), 2018. DOI: https://doi.org/10.1186/s12859-018-2350-8  
• D. Dessì, M. Dragoni, M. Marras, & D. Reforgiato Recupero: Analisi Emozionale di recensioni di corsi online basata su Deep Learning e Word Embeddings. In Proc. of Conferenza GARR 2018. DOI: 10.26314/GARR-Conf18-proceedings
• D. Dessì, G. Fenu, M. Marras, & D. Reforgiato Recupero: COCO: Semantic-Enriched Collection of Online Courses at Scale with Experimental Use Cases, World Conference on Information Systems and Technologies, Vol 2, 2018, 1386-1396. DOI: https://doi.org/10.1007/978-3-319-77712-2_133

2017

• D. Dessì, D. Reforgiato Recupero, G. Fenu, S. Consoli: Exploiting Cognitive Computing and Frame Semantic Features for Biomedical Document Clustering. In Proc. of the Workshop on Semantic Web Solutions for Large-scale Biomedical Data Analytics (SeWeBMeDA@ESWC) co-located with 14th Extended Semantic Web Conference (ESWC 2017), 20-34. http://ceur-ws.org/Vol-1948/paper3.pdf
• D. Dessì, G. Fenu, M. Marras & D. Reforgiato Recupero: Leveraging Cognitive Computing for Multi-Class Classification of E-Learning Videos. In Proc. of 14th European Semantic Web Conference (ESWC 2017) Satellite Events, Poster Track, 21-25. DOI: https://doi.org/10.1007/978-3-319-70407-4_5
• G. Fenu, P.L. Pau, & D. Dessì: Functional models and extending strategies for ecological networks, Applied Network Science, Vol. 2(10), 2017. DOI: https://doi.org/10.1007/s41109-017-0032-5

2016

• G. Fenu, P.L. Pau, & D. Dessì: Modeling and Extending Ecological Networks Using Land Similarity. In Proc. of the 5th International Workshop on Complex Networks and their Applications (COMPLEX NETWORKS 2016), 709-718. DOI: https://doi.org/10.1007/978-3-319-50901-3_56

• M. Alam, F. Dittmann, M. Niebel, J. Lehmann, D. Dessì, J. F. Morgado, P. von Hartrott, C. Eberl, P. Gumbsch, H. Sack (2020). Towards Digitizing Physical Entities in Materials Science [White paper]. [local copy (PDF)]

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